Objectives. The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Methods. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset. Results. The 30-day mortality rate was 5.36% in the validation dataset (n = 3861), slightly lower than the 6.40% in the development dataset (n = 4044). The NHFD and Nottingham models showed a slightly lower discrimination in the validation dataset compared with the development dataset, but both still displayed moderate discriminative power (c-statistic for NHFD = 0.71, 95% confidence interval (CI) 0.67 to 0.74; Nottingham model = 0.70, 95% CI 0.68 to 0.75). Both models defined similar ranges of predicted mortality risk (1% to 18%) in assessment of calibration. Conclusions. Both models have limitations in predicting mortality for individual patients after hip fracture surgery, but the NHFD risk adjustment model performed as well as the widely-used Nottingham prognostic tool and is therefore a reasonable alternative for risk adjustment in the United Kingdom hip fracture population. Cite this article: Bone Joint Res 2017;6:550–556

Aims. While cementless fixation offers potential advantages over cemented fixation, such as a shorter operating time, concerns linger over its higher cost and increased risk of periprosthetic fractures. If the risk of fracture can be forecasted, it would aid the shared decision-making process related to cementless stems. Our study aimed to develop and validate predictive models of periprosthetic femoral fracture (PPFF) necessitating revision and reoperation after elective total hip arthroplasty (THA). Methods. We included 154,519 primary elective THAs from the Swedish Arthroplasty Register (SAR), encompassing 21 patient-, surgical-, and implant-specific features, for model derivation and validation in predicting 30-day, 60-day, 90-day, and one-year revision and reoperation due to PPFF. Model performance was tested using the area under the curve (AUC), and feature importance was identified in the best-performing algorithm. Results. The Lasso regression excelled in predicting 30-day revisions (area under the receiver operating characteristic curve (AUC) = 0.85), while the Gradient Boosting Machine (GBM) model outperformed other models by a slight margin for all remaining endpoints (AUC range: 0.79 to 0.86). Predictive factors for revision and reoperation were identified, with patient features such as increasing age, higher American Society of Anesthesiologists grade (> III), and World Health Organization obesity classes II to III associated with elevated risks. A preoperative diagnosis of idiopathic necrosis increased revision risk. Concerning implant design, factors such as cementless femoral fixation, reverse-hybrid fixation, hip resurfacing, and small (< 35 mm) or large (> 52 mm) femoral heads increased both revision and reoperation risks. Conclusion. This is the first study to develop machine-learning models to forecast the risk of PPFF necessitating secondary surgery. Future studies are required to externally validate our algorithm and assess its applicability in clinical practice. Cite this article: Bone Joint Res 2025;14(1):46–57

Objectives. This study investigates the reporting of health-related quality of life (HRQoL) in patients following hip fracture. We compare the relative merits and make recommendations for the use for two methods of measuring HRQoL; (i) including patients who died during follow-up and (ii) including survivors only. Methods. The World Hip Trauma Evaluation has previously reported changes in HRQoL using EuroQol-5D for patients with hip fractures. We performed additional analysis to investigate the effect of including or excluding those patients who died during the first four months of the follow-up period. Results. The dataset included 503 patients, 25 of whom died between 30 days and four months of injury. There was a statistically significant difference in 30-day HRQoL between those alive (mean 0.331 and standard deviation (. sd. ) 0.360) and those dead (mean 0.156 and . sd. 0.421) by four months (independent-samples t-test; p 0.022). The estimated difference of 0.175 in HRQoL (95% confidence interval 0.025 to 0.325) was also highly clinically significant. Conclusion. When reporting HRQoL for patients after a hip fracture, excluding patients who die during follow-up leads to an overestimate of the effects of the intervention or treatment pathway. We would recommend that death-adjusted estimates should be used routinely when reporting HRQoL in this population. Cite this article: N. Parsons, X. L. Griffin, J. Achten, T. J. Chesser, S. E. Lamb, M. L. Costa. Modelling and estimation of health-related quality of life after hip fracture: A re-analysis of data from a prospective cohort study. Bone Joint Res 2018;7:1–5

Total hip replacement causes a short-term increase in the risk of mortality. It is important to quantify this and to identify modifiable risk factors so that the risk of post-operative mortality can be minimised. We performed a systematic review and critical evaluation of the current literature on the topic. We identified 32 studies published over the last 10 years which provide either 30-day or 90-day mortality data. We estimate the pooled incidence of mortality during the first 30 and 90 days following hip replacement to be 0.30% (95% CI 0.22 to 0.38) and 0.65% (95% CI 0.50 to 0.81), respectively. We found strong evidence of a temporal trend towards reducing mortality rates despite increasingly co-morbid patients. The risk factors for early mortality most commonly identified are increasing age, male gender and co-morbid conditions, particularly cardiovascular disease. Cardiovascular complications appear to have overtaken fatal pulmonary emboli as the leading cause of death after hip replacement.

Cite this article: Bone Joint Res 2014;3:175–82

Objectives

Fractures of the proximal femur are a common clinical problem, and a number of orthopaedic devices are available for the treatment of such fractures. The objective of this study was to assess the rotational stability, a common failure predictor, of three different rotational control design philosophies: a screw, a helical blade and a deployable crucifix.